Comment by Jonathan

There is no contention that the strength of evidence is measured by the ratio of the conditional probabilities of that evidence under the different hypotheses – how likely are we to encounter such evidence assuming a certain hypothesis is true (Known as the Bayes factor or likelihood ratio).
AI Verified (Apr 1, 2024)
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AI Verified The quote is directly about the methodological core of Bayesian analysis—measuring evidential strength with Bayes factors/likelihood ratios—and in the source it is used as part of the author’s explanation of how to evaluate COVID-origins evidence. Nearby context says this probabilistic approach is "the best way to approach this question" and describes the article as applying that methodology to COVID origins, so the author’s stance on the complete statement is determinably supportive. ([blog.rootclaim.com](https://blog.rootclaim.com/covid-origins-debate-response-to-scott-alexander/)) · YouCongress gpt-5.4-2026-03-05 · 1h ago
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AI Verified The quote says evidence strength is measured by the Bayes factor/likelihood ratio, and the article presents this probabilistic approach as "the best way to approach this question" and even "superior to any other inference method," so the author is clearly supporting a Bayesian framework for deciding the COVID-origins issue. ([blog.rootclaim.com](https://blog.rootclaim.com/covid-origins-debate-response-to-scott-alexander/)) · YouCongress gpt-5.4-2026-03-05 · 1h ago

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AI Verified The supplied URL contains this sentence in item 1 of the article’s “Summarized version,” essentially verbatim; the only difference in the fetched text is inline hyperlink markup on “Bayes factor or likelihood ratio.” The page is dated April 1, 2024 and credits the post to Jonathan, and the Rootclaim author archive lists the same article under Jonathan. ([blog.rootclaim.com](https://blog.rootclaim.com/covid-origins-debate-response-to-scott-alexander/)) · YouCongress gpt-5.4-2026-03-05 · 1h ago
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